Category: 1st authorship papers

The GRoLTS-Checklist: Guidelines for Reporting on Latent Trajectory Studies

Estimating models within the mixture model framework, like latent growth mixture modeling (LGMM) or latent class growth analysis (LCGA), involves making various decisions throughout the estimation process. This has led to a wide variety in how results of latent trajectory analysis are reported.

Analyzing small data sets using Bayesian estimation: the case of posttraumatic stress symptoms following mechanical ventilation in burn survivors

The analysis of small data sets in longitudinal studies can lead to power issues and often suffers from biased parameter values. These issues can be solved by using Bayesian estimation in conjunction with informative prior distributions.

Facing off with Scylla and Charybdis: a comparison of scalar, partial, and the novel possibility of approximate measurement invariance

Measurement invariance (MI) is a pre-requisite for comparing latent variable scores across groups. The current paper introduces the concept of approximate MI building on the work of Muthén and Asparouhov and their application of Bayesian Structural Equation Modeling (BSEM) in the software Mplus.

What Took Them So Long? Explaining PhD Delays among Doctoral Candidates

A delay in PhD completion, while likely undesirable for PhD candidates, can also be detrimental to universities if and when PhD delay leads to attrition/termination. Termination of the PhD trajectory can lead to individual stress, a loss of valuable time and resources invested in the candidate and can also mean a loss of competitive advantage.

Bayesian evaluation of informative hypotheses in SEM using Mplus: A black bear story

Half in jest we use a story about a black bear to illustrate that there are some discrepancies between the formal use of the p-value and the way it is often used in practice. We argue that more can be learned from data by evaluating informative hypotheses, than by testing the traditional null hypothesis.